基于神经网络的自适应噪声抵消技术研究

Research on Adaptive Noise Cancellation Based on Neural Network

随着人们生活条件和环境的变化,近年来噪声已经严重影响人们的生活。对于噪声的影响,最重要的就是及时、准确地对其进行防控和消除。传统自适应的噪声消除技术具有极大的局限性,无法解决输入的两路噪声信号间非线性相关问题。基于神经网络的自适应噪声消除技术可以很好地消除噪声源未知时噪声的影响。实验采用BP神经网络算法,结合传统的自适应噪声抵消系统,建立了基于BP神经网络的自适应噪声消除器。利用MATLAB进行了Simulink模块仿真,发现噪声消除的准确率较高,具有非常重要的意义。

With the changes of people's living conditions and environment,noise has seriously affected people's life in recent years.For the influence of noise,the most important thing is to control and eliminate it timely and accurately.The traditional adaptive noise elimination technique has great limitation and cannot solve the non-linear correlation between the input noise signals.The adaptive noise elimination technique based on neural network can eliminate the influence of noise when the noise source is unknown.Based on BP neural network algorithm and traditional adaptive noise cancellation system,adaptive noise canceller based on BP neural network is established.MATLAB is used to simulate the Simulink module,it is very important to find that the accuracy of noise elimination is high.